Video processing, where video image data is processed to ‘improve’ the image is applied in many devices. Furthermore image quality can be improved by the use of video processing in the form of a noise reduction block or processor to reduce noise in the image.
The video noise reduction block can often be the first stage of any video processing pipeline, where the video image frames are noise reduced before any other processing and enhancements in the digital domain are applied. For example noise reduction can be employed for television applications, where in the video signal can be input or received from any one of radio frequency (RF) channel, component input channel, a high definition multimedia interface (HDMI), a composite (CVBS) channel, and s-video input channel.
Noise reduction can for example be spatial or temporal noise reduction. Spatial noise reduction is where areas surrounding a picture element (or pixel) or block of pixels on the same field or frame can be analysed to determine whether the pixel is similar to the surrounding areas and whether a correction or noise reduction operation can be carried out. The noise reduction operation can be for example an averaging across displayed lines or within a line (intraline and interline noise reduction). Furthermore temporal noise reduction is where a pixel is compared to proceeding or succeeding fields or frame pixels to determine whether or not the area pixel differs significantly from previous or following fields or frames, and whether an averaging or filtering across fields or frames should be carried out. Temporal noise reduction requires previous frames or fields to be stored in order that they can be compared to the current frame or field to determine whether there is image motion.
To reduce the memory size required to store the previous frames or fields, aggressive compression modes such as REMPEG are typically performed. The application of REMPEG compression modes introduce an average error of 35 for a 10 bit domain (i.e. an average error of 35 in the range 0 to 1023) at the high frequency regions or edges. This error can create false motion detection in still image regions, and therefore reduce temporal noise reduction application. This reduces the beneficial effect of temporal noise reduction (TNR) and causes noise reduction to be biased towards applying spatial noise reduction (SNR).
Any such low noise still images in such examples can have greater noise levels when aggressive compression is used as less noise reduction is applied and the images suffers resolution loss.